• Optimization typically requires more iterations as the number of design variables increases. You should therefore use as few design variables as possible. Sensitivity studies are helpful in deciding which design variables are important. In particular, local sensitivity studies help identify design variables that do not affect the design significantly.

• The smaller the design space being considered, the shorter the optimization run time. You should therefore use the results from the global sensitivity study to narrow the range of each design variable being considered and thus limit the overall design space.

• The optimization takes less time the closer the baseline model is to the optimum. You might find it useful to review results from sensitivity studies to improve the candidate design prior to optimization.